In support of this idea, we have developed a model of esophageal cancer cell exposure to cigarette smoke condensate (CSC) and deoxycholic acid (DCA) both separately and in combination. To develop the model, the previously published concentrations of CSC by Dr. David S. Schrump's laboratory were tested by proliferation and viability assays in esophageal cancer cells. Appropriate control genes, such as ABCG2 and CYP1A1 were induced. Next, dosage and time for DCA exposure were tested by proliferation and viability assays. The same controls were evaluated which lead to induction with DCA similarly to CSC. Finally, the DCA and CSC were tested synergistically. To evaluate the synergy of DCA and CSC, the cellular metabolic outputs of lactate and ATP were tested. Cancer cells often shift metabolic utilization of glucose from mitochondrial respiration which produces 36 ATP molecules to aerobic glycolysis which produces 2 ATP molecules (Warburg phenomenon). Mitochondrial respiration will increase ATP in the cellular media whereas glycolysis increases lactate production. We noted that a synergistic decrease in lactate and increase in ATP occurs in esophageal cancer cells when treated with both DCA and CSC which suggests the induction of the Warburg phenomena. In addition, gene expression and immunoblot analysis reveal a synergistic reduction in uncoupled protein 2 (UCP2). This protein has been reported to transport nutrients across the mitochondrial membrane to fuel mitochondrial respiration. The reduction in this protein suggests a mechanism by which DCA and CSC induce a malignant phenotype in esophageal cancer cells. We plan to further explore this mechanism by studying the cellular respiration on the Seahorse machine (which measures oxygen utilization and acid production by a living cell in real time). In addition, we plan to complete ongoing functional assays. Once this model has been clearly established, we will evaluate the global metabolic output to determine whether we can identify a metabolic signature that is associated with increased aggressiveness. This metabolic signature will be in conjunction with clinical protocols under development to establish whether a metabolic signature can be discovered that predicts response to therapy in patients.